× Welcome to frontrun me, the premier site for visualizing Ethereum gas auctions. These gas auctions are often bids by frontrunners, arbitrageurs, and other programmatic network actors that seek to exploit inefficiencies in on-chain systems, ultimately profiting miners. On this site, we monitor these behaviors on the network in real-time as these bots compete for block priority in rapid-fire all-pay auctions*, showing users and mechanism designers the potential rent-seeking economy created by orderbook inefficiencies on-chain. Timing data is sourced from a global network of 8 nodes peered deeply with Ethereum. Read our full paper!
*Modern auctions are a special kind of all-pay auction, in which the winner of the auction pays some constant percentage of their bid; they do not pay full gas, as they do not pay for execution, but they must pay for attempted execution.

WARNING: THIS IS AN ALPHA VERSION OF THE SITE WITH PRELIMINARY DATA AND KNOWN BUGS. Use at your own risk and follow @ProjectChicago_ for announcements on release and more data being added.

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Individual Real-Time Auction Data


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Note: only auctions with a single detected "winner" (mined with 2+ log events) are displayed in this view. Other auctions may contain multiple sub-auctions, as the split is heuristic.

Gas Auction #886 - 2018-10-10 06:58:58 to 06:59:01; Start Time 1539154738.9279704

Seconds Elapsed Gas Price (gwei) Bidder (Sender Address/Nonce) Gas Limit Transaction Hash Gas Paid Block/Index Mined
0.000 21.841000000 () 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/935 191957 0x1118fb3a4d02016e579b25dbb7329f145f55380e49df34c63f1af99581c3e40c
0.190 21.841000001 (4.578544938313755e-09) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13110 347815 0xb18f94e41b0649389a20543d9879f16f326e645efc0330f2c9ce3f261237bb47
0.276 24.680330000 (12.206572765391561) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/935 227406 0xd49c4bb960b675ca6e628954644c29e69de701bef9dbe4f2f56d074c315341f7
0.382 27.148363002 (9.523809531159745) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13110 347815 0xd07babe0171bd904e66710c03db429cb677f7a5c7c72a96054b836da50b59fe4
0.387 27.888772900 (2.6905829522756624) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/935 227406 0xf142b00954cbd59b7041599a18e142c88c17aec1e384f19b95d065817e350aa4
0.539 32.849519234 (16.334823254679826) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13110 347815 0xa089e8b125c57b97f9855db23943eb1ec41b5dc49e781d7a60e700a2ed918a51
0.547 32.915218272 (0.1998001983783665) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/935 227406 0x58868ed27893140209c5e0626712b4a97a8c6a7b071397a56369ea1766a589c9
0.710 39.747918274 (18.806509949304218) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13110 347815 0x9558af594e3c3b6b581df60609a28036d628cab6af9ff7d053582bf7617310c2
0.720 39.827414110 (0.1998001984242645) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/935 227406 0x7a3baeaba7fb72a12285e377631b603a50023341de3a4a3f412f125ddca0d4ec
0.867 48.094981113 (18.80650995012304) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13110 347815 0x1c5e00c8dd8ec61d7b871a3becf7bd61907f54b3303e05bacf3331bbe362e110
0.879 48.191171075 (0.1998001993312347) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/935 227406 0xab0cdac05a7d6229da52d19b30ccf7f1706cf5fdd714d900766efc546fa7d663
1.032 58.194927148 (18.806509948378295) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13110 347815 0xd3f1786f02a53dcb751c0a279a0bdd05e1fac39a3e796592948a23c35e5b7444
1.051 58.311317002 (0.19980019929258017) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/935 227406 0x0404096450cdb8d0d0d952c512270f96fb4a1a6a005bbf7d244c8ff77b89d49b
1.150 70.415861850 (18.806509947548555) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13110 347815 0xb20f74f82a72ca307353188b9aa07f2d1371be855ece4dc31795b2d8ca62d6a2
1.188 70.556693573 (0.1998001988080908) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/935 227406 0xb30f204c5c7e13f90ac119e4217bc759fa35e6f5a37c2f561fe0ba1767996733
1.378 85.203192840 (18.80650994847872) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13110 347815 0xe4d09c6de65bcd0a9608b28da4f53dcf9efd726d73c006b7a35da6e2d67c974b
1.444 85.373599225 (0.19980019900370144) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/935 227406 0xb5ad31d9335ce75738dace879a590efc924216be60ad1d0dfa38dbef8a1ec186
1.655 103.095863338 (18.80650994807814) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13110 347815 0x3a14a661a707015928679324c9f078abeed97acef5158c38fe2e6072a7d873c5
1.677 103.302055064 (0.1998001991458088) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/935 227406 0xf65a47597eab92bc6439a5ae1116f9dbf358d95671f3f582b2ce09d321bca0c4
1.846 124.745994640 (18.80650994720949) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13110 347815 0x34818bc050e6ab6f99ab0c5e64dc8e847c052f72ccda235ab55b1481d605eacd
1.873 124.995486629 (0.1998001995761919) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/935 227406 0xcffc6bdb03c079373051181d739f4332e8134180cd5b7f1499edf29a3ca3d1ab
2.050 137.220594105 (9.324452902948789) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13110 347815 0x8afd80e12d91362eeb4c68bcbefc215704a9ef1c8c01f2f67916317182b0f294
2.059 141.244899890 (2.8903443132327618) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/935 227406 0x800541b3b286fa8dbe9f1185d9ce73bd4f64a728824cbd32705ab7a727c9bddc
2.193 150.942653516 (6.6380333542303855) 0x67d1f31eeEF182cFB40c0719A8c0000fA7DDCAA9/13110 347815 0x6380859376772a57c0fd0d2ca34babc67e9f9546de12dffe3d634f9f8a517a09
2.200 159.606736875 (5.5798424515285046) 0x6BEcAb24Ed88Ec13D0A18f20e7dC5E4d5b146542/935 227406 0xbc46f1a10176d76447ac41f328e2523d9d464ba897d646493b2353b6642441f4 6487467 6487467 / 2
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This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No. DGE-1650441.
We would also like to thank NSF CNS-1330599, CNS-1514163, CNS-1564102, and CNS-1704615, ARL W911NF-16-1-0145, and IC3 Industry Partners.
Any opinion, findings, and conclusions or recommendations expressed in this material are those of the authors(s) and do not necessarily reflect the views of the National Science Foundation.